Borrowing it
Nothing to install: this file belongs to compozy/skeeper. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/compozy/skeeper/main/.agents/skills/adversarial-review/SKILL.mdgit clone --depth 1 https://github.com/compozy/skeeperWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/compozy/skeeper/adversarial-review)<a href="https://agentmods.dev/skills/compozy/skeeper/adversarial-review"><img src="https://agentmods.dev/badge/skills/compozy/skeeper/adversarial-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/compozy/skeeper/adversarial-review"><img src="https://agentmods.dev/badge/skills/compozy/skeeper/adversarial-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00056 | $0.01173 |
| Opus 5.5 | $0.00022 | $0.00469 |
| Sonnet 5.5 | $0.00011 | $0.00235 |
| Haiku 4.5 | $0.00006 | $0.00117 |
Grade A, and why
adversarial-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
89% identical to adversarial-review — 20 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adversarial Review
Spawn reviewers on the opposite model to challenge work. Reviewers attack from distinct lenses grounded in brain principles. The deliverable is a synthesized verdict — do NOT make changes.
Hard constraint: Reviewers MUST run via the opposite model's CLI (codex exec or
claude -p). Do NOT use subagents, the Agent tool, or any internal delegation mechanism as
reviewers — those run on your own model, which defeats the purpose.
Step 1 — Load Principles
Read brain/principles.md. Follow every [[wikilink]] and read each linked principle file.
These govern reviewer judgments.
Step 2 — Determine Scope and Intent
Identify what to review from context (recent diffs, referenced plans, user message).
Determine the intent — what the author is trying to achieve. This is critical: reviewers challenge whether the work achieves the intent well, not whether the intent is correct. State the intent explicitly before proceeding.
Assess change size:
| Size | Threshold | Reviewers |
|---|---|---|
| Small | < 50 lines, 1–2 files | 1 (Skeptic) |
| Medium | 50–200 lines, 3–5 files | 2 (Skeptic + Architect) |
| Large | 200+ lines or 5+ files | 3 (Skeptic + Architect + Minimalist) |
Read references/reviewer-lenses.md for lens definitions.
Step 3 — Detect Model and Spawn Reviewers
Create a temp directory for reviewer output:
REVIEW_DIR=$(mktemp -d /tmp/adversarial-review.XXXXXX)
Determine which model you are, then spawn reviewers on the opposite:
If you are Claude → spawn Codex reviewers via codex exec:
codex exec --skip-git-repo-check -o "$REVIEW_DIR/skeptic.md" "prompt" 2>/dev/null
Use --profile edit only if the reviewer needs to run tests. Default to read-only.
Run with run_in_background: true, monitor via TaskOutput with block: true, timeout: 600000.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 141 lines · 56 tokens per session scan A 99f068425a67
adversarial-review is a skill published in the GitHub repository compozy/skeeper (89 stars, last pushed 4mo ago), licensed MIT. It adds 56 tokens to every session and 1,173 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 89% identical to adversarial-review, differing in 20 lines, and is treated as a copy.
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